What is qualitative research?

Qualitative researchers are interested in evaluating,
interpreting and explaining social phenomena. They analyze unstructured
or semi-structured data like interviews, field notes, audio visual material
and journal articles—and they work in a range of sectors; from social
science and education to healthcare and business.

Researchers usually adopt a qualitative methodology
to suit their research question. For
example, a social scientist wanting to develop new concepts or theories
may take a ‘grounded theory’ approach. A researcher looking for ways to
improve health policy or program design might use ‘evaluation methods’.
NVivo doesn’t favor a particular methodology—it’s designed to facilitate
common qualitative techniques no matter what method you use.

Remember that NVivo can help you to manage, explore
and find patterns in your data but it cannot replace your analytical expertise.

Qualitative research as an iterative process

Handling qualitative data is not usually a step-by-step
process (first import,
then code, then
query, then interpret and then write-up). Instead, it tends to
be an iterative process where you explore, code, reflect, memo, code some
more, query and so on. For example, this illustration shows a path you
might take to investigate an interesting theme:

Make
a project journal and state your research questions and record
your goals. Why are you doing the project? What is it about? What
do you expect to find and why? What biases do you bring to the project?
Update the journal regularly to stay focused and to show the evolution
of your project.

Working toward outcomes that are robust and transparent

Qualitative researchers are often called upon to demonstrate
the credibility of their findings—NVivo can help in the following ways:

Was an issue or theme
reported by more than one participant? Run a Matrix
Coding query to see how many participants talked about a theme.

Were multiple methods
used to collect the data (interviews, observations, surveys)—and are
the findings supported across these data sources? Run a Matrix Coding
query to see how often a theme is reported across all your sources

Using NVivo to organize and analyze your data also
increases the 'transparency' of your research outcomes—for example, you
can:

Demonstrate
the evolution of your ideas in memos.

Document
your early preconceptions and biases in a memo and demonstrate how
these have been acknowledged and tested.

Easily find illustrative
quotes.

Always return to the
original context of your coded material.

Save and revisit the
queries that helped you to arrive at your conclusions.